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Figure 1. The human mutation spectrum.

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1 Figure 1. The human mutation spectrum.
From: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment Brief Bioinform. 2015;17(5): doi: /bib/bbv084 Brief Bioinform | © The Author Published by Oxford University Press. For Permissions, please

2 Figure 2. Examples of the coding (functional) and noncoding (regulatory) variants. (i) Functional variant (Pro33Ser) in RRM2B associated with autosomal recessive progressive external ophthalmoplegia visualized on a protein structure (PDB ID: 2vux; Quaternary assembly is generated using PISA/PDBe). Functional variant (Pro33Ser) is highlighted in red color inside the green circle on chains A (part of loop) and B (part of helix). Visualization was created using UCSF Chimera ( ). (ii) Protein domain architectures and functional variants mapped to ii (a) RRM2B and ii (b) ZC3HC1. Ribonuc_red_sm = Ribonucleotide reductase domain; zf = C3HC zinc finger-like domain; Rsm1 = Rsm1-like domain. Functional variants are highlighted using red vertical line. Figure was generated using MyDomains ( ). (iii) Genomic localization of the regulatory variants (a) rs and (b) rs The location of the variants are highlighted using a vertical red line. Regulatory variant rs regulated the expression of nearby genes CDKN2A and CDKN2B (highlighted in red boxes). Intergenic variant rs located between FLJ36031 (CCDC71L)-PIK3CG is located in a TFBS of EVI1 that regulates the expression (repress) of PIK3CG. Genomic regions were visualized using Ensembl Genome Browser v. 67. From: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment Brief Bioinform. 2015;17(5): doi: /bib/bbv084 Brief Bioinform | © The Author Published by Oxford University Press. For Permissions, please

3 Figure 3. Proportional Venn diagram of genes with coding variants annotated as polymorphism (Polymorphism, n  = 11 527), disease (Disease, n  = 2105) and unclassified (Unclassified, n  = 1910) in Human polymorphisms and disease mutations index. Percentages of genes shared between the three groups are provided. From: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment Brief Bioinform. 2015;17(5): doi: /bib/bbv084 Brief Bioinform | © The Author Published by Oxford University Press. For Permissions, please

4 Figure 4. Histograms depicting the distribution (in percentage) of: ( A ) unassigned regions and ( B ) LCRs in the human proteome. From: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment Brief Bioinform. 2015;17(5): doi: /bib/bbv084 Brief Bioinform | © The Author Published by Oxford University Press. For Permissions, please

5 Figure 5. Examples of IDRs in human proteins: ( A ) Breast cancer type 1 susceptibility protein (BRCA1), ( B ) Cellular tumor antigen p53 (Oncoprotein p53), ( C ) T-cell surface glycoprotein CD4 (Disprot), ( D ) Secondary structure information (UniProtKB) and ( E ) mutation histogram (COSMIC) of BRCA1 is provided to illustrate mutations in the unstructured regions. From: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment Brief Bioinform. 2015;17(5): doi: /bib/bbv084 Brief Bioinform | © The Author Published by Oxford University Press. For Permissions, please

6 Figure 6. Schematic representation of the impact of functional mutation on protein misfolding, folding, aggregation, domain swapping, macromolecular crowding and protein degradation pathways. Structure of misfolded rat CD2 structure (PDB ID: 1A6P) and normal CD2 (PDB ID: 1HNG) is used for representing misfolded and folded structures. Functional variant is represented using red asterisk. From: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment Brief Bioinform. 2015;17(5): doi: /bib/bbv084 Brief Bioinform | © The Author Published by Oxford University Press. For Permissions, please

7 Figure 7. Three-level schema for annotation of functional variants.
From: Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment Brief Bioinform. 2015;17(5): doi: /bib/bbv084 Brief Bioinform | © The Author Published by Oxford University Press. For Permissions, please

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